GEOS-DP-001 — Data Pipeline Conceptual Model

Version: 1.0 (Initial Publication) Status: Normative Standard (Conceptual)

0. Interpretive Basis ————————-

GEOS-DP-001 defines the conceptual model for a GEOS-certifiabl Data Pipeline.

This document establishes:

• what a Data Pipeline is under GEOS,

• how it is bounded,

• what kinds of artifacts it produces and consumes, and

• how it relates to other GEOS-certified artifacts.

This document:

• defines no technical implementation requirements;

• defines no certification criteria;

• defines no data standards;

• does not certify Data Sources; and

• does not alter any existing GEOS outcome, signal, or portfolio standards.

Its sole purpose is to define the conceptual object that subsequent GEOS-DP standards will specify and certify.

1. Purpose ————--

The purpose of this standard is to introduce a technology-independent, auditable abstraction—the Data Pipeline—that GEOS can certify as a finance-grade transformation pathway from raw educational data to outcome-relevant aggregates.

A Data Pipeline enables GEOS to:

• reason precisely about how data moves and transforms;

• define certification requirements at the artifact level rather than the institutional level; and

• support Results-Based Funding for Education (RBF4Ed) without asserting control over pedagogy, curriculum, or data ownership.

2. Definition of a Data Pipeline ————————————

A Data Pipeline is a bounded, declarative artifact that specifies:

a controlled sequence of data handling stages that transforms input data received at a defined Entry into output data emitted at a defined Exit, under reproducible, auditable rules.

A Data Pipeline is:

• finite (has explicit boundaries),

• directional (Entry → Exit),

• closed (no data enters or exits except through declared interfaces), and

• inspectable (its structure and transformations can be examined independently of implementation).

3. What a Data Pipeline Is Not ———————————-

A Data Pipeline is not:

• a data source;

• a data collection instrument;

• a software system;

• a runtime environment;

• a database;

• an organization; or

• a governance body.

A Data Pipeline may be implemented by software, manual processes, or hybrid systems, but implementation is out of scope for this standard.

4. Pipeline Boundaries ————————--

4.1 Entry

The Entry of a Data Pipeline is the sole interface through which data enters the pipeline.

Conceptually, the Entry defines:

• the type of data accepted;

• the conditions under which data is accepted; and

• the assumptions the pipeline makes about incoming data.

This standard does not define or constrain:

• how data is generated prior to Entry; or

• who or what supplies the data.

Future GEOS standards may define certification regimes for Data Sources that emit data compatible with a pipeline's Entry, but such regimes are explicitly out of scope here.

4.2 Exit

The Exit of a Data Pipeline is the sole interface through which data leaves the pipeline.

Conceptually, the Exit defines:

• the form of data produced;

• the level of aggregation and depersonalization; and

• the intended downstream use of the output.

Data emitted at the Exit may be:

• used as input to Outcome Signal construction;

• incorporated into an Outcome Signal Portfolio; or

• subjected to independent audit and conformity assessment.

5. Internal Stages (Conceptual) ———————————--

Between Entry and Exit, a Data Pipeline consists of one or more internal stages, each of which performs a well-defined function such as:

• validation,

• normalization,

• aggregation,

• depersonalization,

• transformation, or

• statistical summarization.

This document does not prescribe:

• how many stages exist;

• what they are called; or

• how they are implemented.

It establishes only that:

• all stages are declared;

• all transformations are deterministic or reproducible; and

• no undeclared data flows occur.

6. Relationship to GEOS Outcome Artifacts ———————————————

A GEOS-certifiable Data Pipeline is upstream of:

• Outcome Signals, and

• Outcome Signal Portfolios (OSPs), including GeOSPs™.

Certification of a Data Pipeline:

• does not imply certification of any Outcome Signal or Portfolio; and

• does not replace outcome-level certification.

Instead, it provides a trustable substrate upon which outcome artifacts may be constructed and assessed.

7. Technology and Modality Neutrality —————————————--

The Data Pipeline concept is:

• technology-neutral;

• modality-neutral; and

• implementation-agnostic.

A Data Pipeline may be realized using:

• digital systems,

• manual processes,

• paper-based workflows, or

• hybrid arrangements,

provided that the pipeline's declared structure, transformations, and boundaries can be audited and reconstructed.

8. Forward Compatibility with Data Source Certification ———————————————————--

This conceptual model is intentionally designed so that:

• future GEOS standards may define certification of Data Sources;

• such standards would reference the Entry requirements of a Data Pipeline; and

• no changes to the Data Pipeline conceptual model would be required.

The Data Pipeline remains the primary certifiable transformation artifact, regardless of whether Data Sources are later certified.

9. Scope Limits ——————-

GEOS-DP-001 does not

• define finance eligibility;

• mandate disclosure;

• constrain School Systems;

• assert data ownership; or

• impose operational requirements on any actor.

It defines only the conceptual object that later GEOS-DP standards will specify, assess, and certify.

End of GEOS-DP-001